A Comprehensive Visual Analytics Study of the Global AI Job Market: Salary Trends, Experience Requirements, and Remote Work Opportunities

The rapid expansion of artificial intelligence (AI) technologies has led to an increasing demand for skilled professionals across various industries. Understanding job market dynamics such as salary distribution, experience requirements, employment types, and remote work opportunities is crucial for students, job seekers, educators, and policymakers. This research presents a comprehensive visual analytics study of the global AI job market using a real-world dataset consisting of approximately 15,000 job postings. The dataset includes variables such as job titles, salaries in USD, experience levels, employment types, company locations, employee residence, remote work ratios, industry sectors, and benefits scores. Building on established visual analytics practices in employment and public-health data analysis, this study applies a range of exploratory tasks used in prior research, including trend identification, comparison across categories, correlation analysis, and outlier detection. Visualization techniques such as bar charts, box plots, scatter plots, line graphs, violin plots, and heatmaps are employed to explore patterns and relationships within the data. The analysis shows that salary is strongly correlated with experience level and geographic location. Senior-level professionals earn significantly more than entry-level employees, while countries such as the United States, Switzerland, and Canada offer the highest compensation. In addition, remote and hybrid work arrangements are increasingly prevalent and, in some cases, associated with higher average salaries. The study supports career decision-making by enabling stakeholders to identify high-paying regions, realistic experience pathways, and industries with strong AI demand.